Magnetic resonance spectroscopy (MRS) is capable of revealing important biochemical and metabolic information of tissues noninvasively. However, the low concentrations of metabolites often lead to poor signal-to-noise ratio (SNR) and a long acquisition time. Therefore, the applications of MRS in detection and quantitative measurements of metabolites in vivo remain limited. Reducing or even eliminating noise can improve SNR sufficiently to obtain high quality spectra in addition to increasing the number of signal averaging (NSA) or the field strength, both of which are limited in clinical applications. We present a Spectral Wavelet-feature ANalysis and Classification Assisted Denoising (SWANCAD) approach to differentiate signal and noise peaks in magnetic resonance spectra based on their respective wavelet features, followed by removing the identified noise components to improve SNR. The performance of this new denoising approach was evaluated by measuring and comparing SNRs and quantified metabolite levels of low NSA spectra (e.g. NSA = 8) before and after denoising using the SWANCAD approach or by conventional spectral fitting and denoising methods, such as LCModel and wavelet threshold methods, as well as the high NSA spectra (e.g. NSA = 192) recorded in the same sampling volumes. The results demonstrated that SWANCAD offers a more effective way to detect the signals and improve SNR by removing noise from the noisy spectra collected with low NSA or in the subminute scan time (e.g. NSA = 8 or 16 s). The potential applications of SWANCAD include using low NSA to accelerate MRS acquisition while maintaining adequate spectroscopic information for detection and quantification of the metabolites of interest when a limited time is available for an MRS examination in the clinical setting.
Background
Adiposity and mitochondrial dysfunction are related factors contributing to metabolic disease development. This pilot study examined whether in vivo and ex vivo indices of mitochondrial metabolism were differentially associated with body composition in males and females.
Methods
Thirty-four participants including 19 females (mean 27 yr) and 15 males (mean 29 yr) had body composition assessed by dual energy x-ray absorptiometry and magnetic resonance (MR) imaging. Monocyte reserve capacity and maximal oxygen consumption rate (OCR) were determined ex vivo using extracellular flux analysis. In vivo quadriceps mitochondrial function was measured using 31P-MR spectroscopy based on post-exercise recovery kinetics (τPCr). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated from fasting glucose and insulin levels. Variables were log-transformed, and Pearson correlations and partial correlations were used for analyses.
Results
Mitochondrial metabolism was similar between sexes (p > 0.05). In males only, higher fat mass percent (FM%) was correlated with lower reserve capacity (r = − 0.73; p = 0.002) and reduced muscle mitochondrial function (r = 0.58, p = 0.02). Thigh subcutaneous adipose tissue was inversely related to reserve capacity in males (r = − 0.75, p = 0.001), but in females was correlated to higher maximal OCR (r = 0.48, p = 0.046), independent of FM. In females, lean mass was related to greater reserve capacity (r = 0.47, p = 0.04). In all participants, insulin (r = 0.35; p = 0.04) and HOMA-IR (r = 0.34; p = 0.05) were associated with a higher τPCr.
Conclusions
These novel findings demonstrate distinct sex-dependent associations between monocyte and skeletal muscle mitochondrial metabolism with body composition. With further study, increased understanding of these relationships may inform sex-specific interventions to improve mitochondrial function and metabolic health.
by
Tyrone D. Cannon;
Frank Sun;
Sarah Jacobson McEwen;
Xenophon Papademetris;
George He;
Theo G. M. van Erp;
Aron Jacobson;
Carrie E. Bearden;
Elaine Walker;
Xiaoping Hu;
Lei Zhou;
Larry J. Seidman;
Heidi W. Thermenos;
Barbara Cornblatt;
Doreen M. Olvet;
Diana Perkins;
Aysenil Belger;
Kristin Cadenhead;
Ming Tsuang;
Heline Mirzakhanian;
Jean Addington;
Richard Frayne;
Scott W. Woods;
Thomas H. McGlashan;
R. Todd Constable;
Maolin Qiu;
Daniel H. Mathalon;
Paul Thompson;
Arthur W. Toga
Multisite longitudinal neuroimaging designs are used to identify differential brain structural change associated with onset or progression of disease. The reliability of neuroanatomical measurements over time and across sites is a crucial aspect of power in such studies. Prior work has found that while within-site reliabilities of neuroanatomical measurements are excellent, between-site reliability is generally more modest. Factors that may increase between-site reliability include standardization of scanner platform and sequence parameters and correction for between-scanner variations in gradient nonlinearities. Factors that may improve both between- and within-site reliability include use of registration algorithms that account for individual differences in cortical patterning and shape. In this study 8 healthy volunteers were scanned twice on successive days at 8 sites participating in the North American Prodrome Longitudinal Study (NAPLS). All sites employed 3 Tesla scanners and standardized acquisition parameters. Site accounted for 2 to 30% of the total variance in neuroanatomical measurements. However, site-related variations were trivial (<1%) among sites using the same scanner model and 12-channel coil or when correcting for between-scanner differences in gradient nonlinearity and scaling. Adjusting for individual differences in sulcal-gyral geometries yielded measurements with greater reliabilities than those obtained using an automated approach. Neuroimaging can be performed across multiple sites at the same level of reliability as at a single site, achieving within- and between-site reliabilities of 0.95 or greater for gray matter density in the majority of voxels in the prefrontal and temporal cortical surfaces as well as for the volumes of most subcortical structures.
Mechanism-based inhibitors of enzymes, which mimic reactive intermediates in the reaction pathway, have been deployed extensively in the analysis of metabolic pathways and as candidate drugs. The inhibition of cytosine-[C5]-specific DNA methyltransferases (C5 MTases) by oligodeoxynucleotides containing 5-azadeoxycytidine (AzadC) and 5-fluorodeoxycytidine (FdC) provides a well-documented example of mechanism-based inhibition of enzymes central to nucleic acid metabolism. Here, we describe the interaction between the C5 MTase from Haemophilus haemolyticus (M.Hha I) and an oligodeoxynucleotide duplex containing 2-H pyrimidinone, an analogue often referred to as zebularine and known to give rise to high-affinity complexes with MTases. X-ray crystallography has demonstrated the formation of a covalent bond between M.Hha I and the 2-H pyrimidinone-containing oligodeoxynucleotide. This observation enables a comparison between the mechanisms of action of 2-H pyrimidinone with other mechanism-based inhibitors such as FdC. This novel complex provides a molecular explanation for the mechanism of action of the anti-cancer drug zebularine.